• Title/Summary/Keyword: online map

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Characterization of Diseasomal Proteins from Human Disease Network (인간 질병 네트워크로부터 얻은 질병 단백체의 특성 분석)

  • Lee, Yoon Kyeong;Ku, Jaeul;Yeo, Myeong Ho;Kang, Tae Ho;Song, MinDong;Yoo, Jae-Soo;Kim, Hak Yong
    • Proceedings of the Korea Contents Association Conference
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    • 2009.05a
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    • pp.306-311
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    • 2009
  • We initially obtained human diseases-related proteins dataset from the OMIM and the SWISS PROT and then constructed disease-related protein-protein interaction network. The protein network contains 40 hub proteins such as CALM1, ACTB and ABL2. The protein network can be derived the map of the relationship between different disease proteins, denoted disease interaction network. We demonstrate that the associations between diseases are directly correlated to their underlying protein-protein interaction networks. From constructed the disease-protein bipartite network, we derived 38 diseasomal proteins, including APP, ABL1 and STAT1. We previously demonstrated that hub proteins in the network tend to be diseasomal proteins in the disease-related protein sub-networks. However, we found that 18% hubs are only diseasomal proteins in the whole disease network. At this point, we could not elucidate difference in the hub-diseasomal proteins tendency between sub0network and whole network. In spite of we still have unsolved problems, our results elucidate that the discovery of protein interaction networks assigned by diseases will provide insight into the underlying molecular mechanisms and biological processes in complex human disease system.

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A Positioning Study of National Food: In Perspective of Korean, American, Chinese Food Tourists (세계음식 브랜드 포지셔닝에 대한 연구: 한국, 미국, 중국 음식관광객을 대상으로)

  • Choi, Ha-Yeon;Kwak, Gong-Ho;Kim, Hak-Seon
    • Culinary science and hospitality research
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    • v.23 no.2
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    • pp.86-94
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    • 2017
  • This study was conducted to derive a positioning map using multidimensional scaling method to understand how the brand image of national foods including Korean food, Chinese food, Japanese food, Thai food, and Vietnamese food is perceived by domestic and foreign tourists. In order to achieve the research purpose, this study collected 250 data through online and offline surveys for potential food tourists who are interested in visiting overseas. Except the unfaithful responses or missing values, 202 data were analyzed. As a result, first, 8 factors which are considered to be important by food tourists were extracted. Second, the result of similarity analysis using ALSCAL and PROXSCAL did not show that the foods of the five countries were very similar, but all countries seemed to be more likely to compete with each other. Third, attribute selection also indicates that mean value of food taste (3.88), national image (3.82), and sufficient food quantity (3.65) had high level of importance, respectively. These results may provide practical implications for development of branding strategy in food tourism.

A Study on the Characteristics of the Spatial Distribution of Sex Crimes: Spatial Analysis based on Environmental Criminology (성폭력 범죄의 공간적 분포 특성에 관한 연구: 환경범죄학에 기반한 공간 분석)

  • Lee, Gunhak;Jin, Chanwoo;Kim, Jiwoo;Kim, Wanhee
    • Journal of the Korean Geographical Society
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    • v.51 no.6
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    • pp.853-871
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    • 2016
  • The interest in the prevention of sex crimes and social secure is growing as the number of cases by sexual offences becomes higher. Although various punishable ways have been introduced so far, increasing sex crime is still going on. Thus, effectiveness of legal systems for preventing crimes is questionable. More recently, the approach for environmental criminology has been paid attention for reducing criminal opportunities through environmental design and management of crimes. This study attempts to look over the spatial distribution of sexual crimes in the context of environmental criminology, and examine the correlation between regional environmental factors and the occurrence of sexual crimes empirically. To do this, we visualized the map for sex crimes at the macro-scale and explored the spatial distribution of sexual crimes and spatial clusters based on various spatial statistics using sex crime data published online by the ministry of gender equality and family. Also, we derived the environmental characteristics of sexual crimes by multivariate regression analysis on a large number of explanatory variables of regional environment. Our results will help to understand the current situation and spatial aspects of sex crimes in the nation more realistically. Further, it is respected that our results might be useful basic information for establishing regional policies and plans for the prevention of the sexual crime and enhanced public policing.

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Enrichment of POI information based on LBSNS (위치기반 소셜 네트워크 서비스(LBSNS)를 이용한 POI 정보 강화 방안)

  • Cho, Sung-Hwan;Ga, Chil-O;Huh, Yong
    • Journal of Cadastre & Land InformatiX
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    • v.48 no.2
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    • pp.109-119
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    • 2018
  • Point of interest (POI) of the city is a special place that has what importance to the user. For example, it is such landmark, restaurants, museums, hotels, and theaters. Because of its role in the social and economic life of us, these have attracted a lot of interest in location-based applications such as social networks and online map. However, while it can easily be obtained through the Web, the basic information of POI such as geographic location, another effort is required to obtain detailed information such as Wi-Fi, accepting credit cards, opening hours, romper room and the assessment and evaluation of other users. To solve these problems, a new method for correcting position error is required to link location-based social network service (LBSNS) data and POIs. This paper attempts to propose a position error correction method of POI and LBSNS data to enrich POI information from the vast information that is accumulated in LBSNS. Through this study, we can overcome the limitation of individual POI information via the information fusion method of LBSNS and POI, and we have discovered the possibility to be able to provide additional information which users need. As a result, we expect to be able to collect a variety of POI information quickly.

Exploring Learning Progressions for Global Warming: Focus on Middle School Level (지구 온난화에 대한 학습발달과정 탐색: 중학교를 중심으로)

  • Yu, Eun-Jeong;Lee, Kiyoung;Kwak, Youngsun;Park, Jaeyong
    • Journal of Science Education
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    • v.46 no.1
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    • pp.1-16
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    • 2022
  • The purpose of this study is to explore learning progressions for global warming at middle school level. For this purpose, we conducted a construct modeling approach that specifies constructs, item designs, outcome spaces, and measurement model steps from April to October, 2021. In order to develop student assessment items, we analyzed the 2015 revised curriculum and textbooks of middle school and categorized a concept hierarchy for each construct to create a construct map. The assessment items were developed into multiple-choice, short answer, and essay questions according to the selected constructs to strengthen the linkage between the constructs and the items. Based on the three-step grading criteria for each item, an online assessment of 21 minor items developed for middle school students show that many students met 'high' level, but none met 'low' level. In this manner, the initial set lower anchor was reset to level 0, the original set upper anchor was lowered from level 4 to level 3, and the hypothetical learning progression for global warming was presented in the following order: phenomenal, conceptual, and mechanical understandings. The results of the research have raised implications for reorganizing the next science curriculum and improving the assessment system.

Digital Barrier-Free and Psychosocial Support for Students with Disabilities in Distance Learning Environments

  • Kravchenko, Oksana;Koliada, Natalia;Berezivska, Larysa;Dikhtyarenko, Svitlana;Baida, Svitlana;Danylevych, Larysa
    • International Journal of Computer Science & Network Security
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    • v.22 no.8
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    • pp.15-24
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    • 2022
  • The article clarifies the conditions for information, digital and educational accessibility for higher education seekers with disabilities in terms of distance learning caused by quarantine restrictions. It is established that such conditions are regulated by international and Ukrainian legal documents (The Standard Rules on the Equalization of Opportunities for Persons with Disabilities, Convention on the Rights of Persons with Disabilities, Sustainable Development Goals, Law of Ukraine "On Education", Law of Ukraine "On Higher Education", Strategy for the Development of Higher Education in Ukraine 2021-2031, Development Strategy areas of innovation for the period up to 2030, Development strategy of the sphere of innovation activity for the period up to 2030). As a part of information barrierlessness, Higher Education Institutions (HEI) should provide access to information in various formats and using technologies, in particular Braille script, large-type printing, audio description (audio descriptive commenting), sign language interpretation, subtitling, a format suitable for reading by screen access programs, formats of simple speech, easy-to-read formats, means of alternative communication. The experience of Pavlo Tychyna Uman State Pedagogical University is described. In particular, special attention is paid to the study of sign language: in view of this, the initiative group implemented the project "Learning to hear and overcome social isolation together" with the financial support of the British Council in Ukraine. Within the framework of digital accessibility, the official website of the Faculty of Social and Psychological Education has been adapted for the visually impaired in accordance with WCAG 2.0 World Standards. In 2021, Pavlo Tychyna Uman State Pedagogical University implemented the project "Cultural, Recreational and Tourist Cherkasy Region: Inclusive Social 3D Map" funded by the Ukrainian Cultural Foundation; a site with available content for online travel in the region to provide barrier-free access to the historical and cultural heritage of Cherkasy region was created. Educational accessibility is achieved by increasing the number of people with special educational needs, receiving education in inclusive groups; activities of the Center for Social and Educational Integration and Inclusive Rehabilitation Social Tourism "Bez barieriv" ("Without barriers"); implementation of a research topic for financing the Ministry of Education and Science of Ukraine: "Social and psychological rehabilitation of children and youth with special educational needs by means of inclusive tourism"; implementation of the project "Social inclusion of distance educational process"; development of information campaigns to popularize the ideas of accessibility, the need for its implementation, ongoing training programs and competitions, etc.

The Impact of Servicescapes of Global Coffee Franchise Store on Customer Satisfaction and Loyalty: The Case Study of 'C' Franchising Company in Mongolia (글로벌 커피 프랜차이즈 전문점의 서비스스케이프가 고객만족과 충성도에 미치는 영향 : 몽골의 'C' 기업의 사례 연구)

  • Samdan, Davaasuren;Han, Young-Wee;An, Dae-Sun
    • The Korean Journal of Franchise Management
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    • v.9 no.3
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    • pp.19-29
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    • 2018
  • Purpose - Due to the increase in coffee consumption and competition, domestic coffee franchise companies are currently entering the overseas market. Therefore, coffee franchise companies are pursuing a variety of marketing strategies to meet customer needs and gain competitive advantage in overseas markets. From this perspective, overseas franchise companies need to ensure that their servicescapes meet the needs of their overseas customers. For these purposes, the study is to identify the impact servicescapes on customer satisfaction and customer loyalty focused on Global Coffee Franchise Company "C", which extended its business worldwide in Mongolia. Research design, data, and methodology - The data were collected from customers who had visited the stores of 'C' company in Ulaanbaatar, Mongolia. 435 valid questionnaires collected through online survey coded and analyzed using frequency, confirmatory factor analysis, correlations analysis, and structural equation modeling with SPSS 24 and SmartPLS 3.0. Result - Firstly, seating comfort, facility aesthetics, and cleanliness, ambient conditions among servicescapes influenced customer satisfaction. Secondly, servicescapes didn't affect the loyalty directly. Third, customer satisfaction had positive effect on loyalty. Fourthly, cleanliness which was ranked lower in Korea had a great effect on customer satisfaction in Mongolia. Fifthly, IPMA(Importance-performance map analysis) shows that the importance of servicescapes is higher for women than for men, and facility aesthetics for female and cleanliness is the most important for male. Conclusions - The results of this study show that there is a positive (+) effect on customer satisfaction in order of cleanliness, ambient conditions, aesthetics, and seating comfort. Therefore, franchise companies considering or advancing into Mongolia should consider importance in order of cleanliness, ambient conditions and aesthetics when entering Mongolia market. For example, franchise managers should select Monday as a "clean day," and all merchants should spend all of their open hours and keep their stores clean in accordance with the head office manual. In addition, franchise managers need to hire a VMD (visual merchandising) experts to build up a physical environment that will effectively highlight the space-specific display of the store so that Mongolian local customers can have a satisfactory climate and aesthetics. And, the IMPA analysis between servicescapes and customer satisfaction shows that women are more susceptible to servicescapes than men. Especially, in the case of women, the importance of esthetics is high, but the performance is low. Thus, if the aesthetics are actively improved, customer satisfaction can be effectively increased.

Investigating the Performance of Bayesian-based Feature Selection and Classification Approach to Social Media Sentiment Analysis (소셜미디어 감성분석을 위한 베이지안 속성 선택과 분류에 대한 연구)

  • Chang Min Kang;Kyun Sun Eo;Kun Chang Lee
    • Information Systems Review
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    • v.24 no.1
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    • pp.1-19
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    • 2022
  • Social media-based communication has become crucial part of our personal and official lives. Therefore, it is no surprise that social media sentiment analysis has emerged an important way of detecting potential customers' sentiment trends for all kinds of companies. However, social media sentiment analysis suffers from huge number of sentiment features obtained in the process of conducting the sentiment analysis. In this sense, this study proposes a novel method by using Bayesian Network. In this model MBFS (Markov Blanket-based Feature Selection) is used to reduce the number of sentiment features. To show the validity of our proposed model, we utilized online review data from Yelp, a famous social media about restaurant, bars, beauty salons evaluation and recommendation. We used a number of benchmarking feature selection methods like correlation-based feature selection, information gain, and gain ratio. A number of machine learning classifiers were also used for our validation tasks, like TAN, NBN, Sons & Spouses BN (Bayesian Network), Augmented Markov Blanket. Furthermore, we conducted Bayesian Network-based what-if analysis to see how the knowledge map between target node and related explanatory nodes could yield meaningful glimpse into what is going on in sentiments underlying the target dataset.

Multi-day Trip Planning System with Collaborative Recommendation (협업적 추천 기반의 여행 계획 시스템)

  • Aprilia, Priska;Oh, Kyeong-Jin;Hong, Myung-Duk;Ga, Myeong-Hyeon;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.22 no.1
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    • pp.159-185
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    • 2016
  • Planning a multi-day trip is a complex, yet time-consuming task. It usually starts with selecting a list of points of interest (POIs) worth visiting and then arranging them into an itinerary, taking into consideration various constraints and preferences. When choosing POIs to visit, one might ask friends to suggest them, search for information on the Web, or seek advice from travel agents; however, those options have their limitations. First, the knowledge of friends is limited to the places they have visited. Second, the tourism information on the internet may be vast, but at the same time, might cause one to invest a lot of time reading and filtering the information. Lastly, travel agents might be biased towards providers of certain travel products when suggesting itineraries. In recent years, many researchers have tried to deal with the huge amount of tourism information available on the internet. They explored the wisdom of the crowd through overwhelming images shared by people on social media sites. Furthermore, trip planning problems are usually formulated as 'Tourist Trip Design Problems', and are solved using various search algorithms with heuristics. Various recommendation systems with various techniques have been set up to cope with the overwhelming tourism information available on the internet. Prediction models of recommendation systems are typically built using a large dataset. However, sometimes such a dataset is not always available. For other models, especially those that require input from people, human computation has emerged as a powerful and inexpensive approach. This study proposes CYTRIP (Crowdsource Your TRIP), a multi-day trip itinerary planning system that draws on the collective intelligence of contributors in recommending POIs. In order to enable the crowd to collaboratively recommend POIs to users, CYTRIP provides a shared workspace. In the shared workspace, the crowd can recommend as many POIs to as many requesters as they can, and they can also vote on the POIs recommended by other people when they find them interesting. In CYTRIP, anyone can make a contribution by recommending POIs to requesters based on requesters' specified preferences. CYTRIP takes input on the recommended POIs to build a multi-day trip itinerary taking into account the user's preferences, the various time constraints, and the locations. The input then becomes a multi-day trip planning problem that is formulated in Planning Domain Definition Language 3 (PDDL3). A sequence of actions formulated in a domain file is used to achieve the goals in the planning problem, which are the recommended POIs to be visited. The multi-day trip planning problem is a highly constrained problem. Sometimes, it is not feasible to visit all the recommended POIs with the limited resources available, such as the time the user can spend. In order to cope with an unachievable goal that can result in no solution for the other goals, CYTRIP selects a set of feasible POIs prior to the planning process. The planning problem is created for the selected POIs and fed into the planner. The solution returned by the planner is then parsed into a multi-day trip itinerary and displayed to the user on a map. The proposed system is implemented as a web-based application built using PHP on a CodeIgniter Web Framework. In order to evaluate the proposed system, an online experiment was conducted. From the online experiment, results show that with the help of the contributors, CYTRIP can plan and generate a multi-day trip itinerary that is tailored to the users' preferences and bound by their constraints, such as location or time constraints. The contributors also find that CYTRIP is a useful tool for collecting POIs from the crowd and planning a multi-day trip.

Perception and Appraisal of Urban Park Users Using Text Mining of Google Maps Review - Cases of Seoul Forest, Boramae Park, Olympic Park - (구글맵리뷰 텍스트마이닝을 활용한 공원 이용자의 인식 및 평가 - 서울숲, 보라매공원, 올림픽공원을 대상으로 -)

  • Lee, Ju-Kyung;Son, Yong-Hoon
    • Journal of the Korean Institute of Landscape Architecture
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    • v.49 no.4
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    • pp.15-29
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    • 2021
  • The study aims to grasp the perception and appraisal of urban park users through text analysis. This study used Google review data provided by Google Maps. Google Maps Review is an online review platform that provides information evaluating locations through social media and provides an understanding of locations from the perspective of general reviewers and regional guides who are registered as members of Google Maps. The study determined if the Google Maps Reviews were useful for extracting meaningful information about the user perceptions and appraisals for parks management plans. The study chose three urban parks in Seoul, South Korea; Seoul Forest, Boramae Park, and Olympic Park. Review data for each of these three parks were collected via web crawling using Python. Through text analysis, the keywords and network structure characteristics for each park were analyzed. The text was analyzed, as were park ratings, and the analysis compared the reviews of residents and foreign tourists. The common keywords found in the review comments for the three parks were "walking", "bicycle", "rest" and "picnic" for activities, "family", "child" and "dogs" for accompanying types, and "playground" and "walking trail" for park facilities. Looking at the characteristics of each park, Seoul Forest shows many outdoor activities based on nature, while the lack of parking spaces and congestion on weekends negatively impacted users. Boramae Park has the appearance of a city park, with various facilities providing numerous activities, but reviewers often cited the park's complexity and the negative aspects in terms of dog walking groups. At Olympic Park, large-scale complex facilities and cultural events were frequently mentioned, emphasizing its entertainment functions. Google Maps Review can function as useful data to identify parks' overall users' experiences and general feelings. Compared to data from other social media sites, Google Maps Review's data provides ratings and understanding factors, including user satisfaction and dissatisfaction.